Tag: learning

Seymour Papert passed away this weekend. His ideas have helped us form the pedagogical approach behind Pedago and our first product, Smartly.

Seymour Papert passed away this weekend, and I felt compelled to revisit his classic book, Mindstorms: Children, Computers, and Powerful Ideas, in tribute. Papert’s legacy far exceeds this one book, of course; he’s an inventor of the Logo programming language, and he was hugely influential in the fields of artificial intelligence, educational technology, and child development over the course of his half-century career. Closer to home, his ideas have helped us form the pedagogical approach behind Pedago and our first product, Smartly.

“We are at a point in the history of education when radical change is possible, and the possibility for that change is directly tied to the impact of the computer.” – Seymour Papert, Mindstorms

Three years ago, my co-founder Ori Ratner and I read Mindstorms outside of his apartment complex in Arlington, VA as we formulated our opinions about what was missing in educational technology. In the early days of the company, we encouraged all new employees to read the book before starting, so that we could all have a shared vision for what was possible.

While the book is nominally about children using computers to learn, it establishes a vision for how anyone—adult or child—can learn. Mindstorms was published in 1980, the same year as Carl Sagan’s Cosmos. Despite the possibility that, like an old science fiction novel, it might have aged past its usefulness, Papert’s prose is inspiring. Certain sections feel revolutionary. The future he had envisioned had still not come to pass, but reading it that summer, it felt just inches away.

Rereading Mindstorms, I’m struck by how poetic the book is.

Parts of Mindstorms read like Cosmos, aimed at distilling complex ideas for consumption by a lay audience. Sagan used philosophical quotes to remind readers that the universe is not just what lies outside of the earth’s atmosphere: they themselves are the universe. “The nitrogen in our DNA, the calcium in our teeth, the iron in our blood, the carbon in our apple pies were made in the interiors of collapsing stars. We are made of starstuff.”

Mindstorms is at times similarly poetic, merging Papert’s musings on his own learning experiences with a glimpse into what successful learning might look like in the future: “You can’t think seriously about thinking without thinking about thinking about something.” He relates a formative example from his young childhood, of imagining what it’s like to be a gear, and describes the impact of that very personal experience on his future learning and mental development. His goal in writing the book and creating Logo was to give more humans an experience of what that’s like.

For me, the reminder of the personal side of learning is one of the most powerful aspects of the book. It’s not just about assimilating information, but about the learner constructing their understanding.

Two Smartly developers mentioning Papert’s Logo as an early coding inspiration.

In honor of Seymour Papert, I want to share some of my favorite passages from the book:

“Anything is easy, if you can assimilate it to your collection of models. If you can’t, anything can be painfully difficult.” (xix)

“People often fear that using computer models for people will lead to mechanical or linear thinking; they worry about people losing respect for their intuitions, sense of values, powers of judgment. They worry about instrumental reason becoming a model for good thinking. I take these fears seriously but do not see them as fears about computers themselves but rather as fears about how culture will assimilate the computer presence.” (155)

“I see the classroom as an artificial and inefficient learning environment that society has been forced to invent because its informal environments fail in certain essential learning domains, such as writing or grammar or school math. I believe that the computer presence will enable us to so modify the learning environment outside the classrooms that much if not all the knowledge schools presently try to teach with such pain and expense and such limited success will be learned, as the child learns to talk, painlessly, successfully, and without organized instruction. This obviously implies that schools as we know them today will have no place in the future. But it is an open question whether they will adapt by transforming themselves into something new or wither away and be replaced.” (8-9)

“…when one enters a new domain of knowledge, one initially encounters a crowd of new ideas. Good learners are able to pick out those who are powerful and congenial. Others who are less skillful need help from teachers and friends. But we must not forget that while good teachers play the role of mutual friends who can provide introductions, the actual job of getting to know an idea or a person cannot be done by a third party. Everyone must acquire skill at getting to know and a personal style for doing it.” (137)

“I do not wish to reduce mathematics to literature or literature to mathematics. But I do want to argue that their respective ways of thinking are not as separate as is usually supposed.” (39)

“There is no end to education. It is not that you read a book, pass an examination and finish with education. The whole of life, from the moment you are born till the moment you die is a process of learning.”

This is the first of two posts delineating the pedagogical approach of Herb Simon, credited with inventing the field of AI, for which he won a Turing award in 1975.

This is the first of two blog posts delineating the pedagogical approach of Herb Simon, the man credited with inventing the field of artificial intelligence, for which he won a Turing award in 1975. Simon was a polyglot social scientist, computer scientist and economics professor at Carnegie Mellon University. He later won the Nobel Prize in 1978 in economics for his work in organizational decision-making.

Herbert Simon, Pittsburg Post Gazette Archives

“Learning results from what the student does and thinks and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn.” –Herb Simon

Among his many accomplishments, Herb Simon was a pioneer in the field of adaptive production systems. He also identified the decision-making strategy “satisficing,” which describes the goal of finding a solution that is “good enough” and which meets an acceptability threshold, as opposed to “optimizing,” which aims to find an ideal solution.

Simon believed that human beings lack the cognitive resources to optimize, and are usually operating under imperfect information or inaccurate probabilities of outcomes. In both computer algorithm optimization and human decision-making, satisficing can save significant resources, as the cost of collecting the additional information needed to make the optimal decision can often exceed the total benefit of the current decision.

We live in a world where overwhelming amounts of information are at our very fingertips. Every month new educational software offerings are on the market. You can find tutorials to fix anything in your house, learn a new language for free, find lessons that teach you to dance, and watch video lectures from top universities in the topics of your choice.

I like to think of myself as a polyglot learner: I would love nothing better than to just take a year, or two, or ten, and learn as much as I can about everything. But unfortunately, I have limited time. How do I know which tutorials, lessons, and classes are worth the commitment of my time? How can I find a satisficing solution to the problem of becoming a more well-rounded learner and human being?

In Simon’s words, “information is not the scarce resource; what is scarce is the time for us humans to attend to it.” At Pedago we’ve been inspired by thinkers such as Simon to build a learning solution that makes the most of the scarce resource of your time, by employing curated streams of bite-sized lessons; rich, explorable connections between topics; interactive learn-by-doing experiences; and just the right amount of gamification. We want to enable you to craft your own learning experience, so that you can, as Simon would say, positively influence what you do and what you think.

Stay tuned for the second post in this series as we examine Simon’s modeling of human learning.

Given how useful the tinkering approach is for keeping learners motivated, how do we apply a similar approach to a subject like Finance?

By Artaxerxes (Own work) [CC-BY-SA-3.0], via Wikimedia CommonsMy friend Alfredo builds bikes as a hobby. He started by replacing a broken chain on his own bike. Then he upgraded his brakes. After a few more repairs, he understood the whole bike system well enough that he could gather all the parts and build one from scratch.

Experienced programmers generally learn new languages in a similar way. We get assigned to a new project for which there is an existing codebase that needs to be maintained or extended. Everything is mostly working, but something needs to be tweaked or added. So we tweak it. After working on five or ten features, we know the new language well enough that we could start a new project ourselves.

In more traditional educational environments, however, we tend to learn things the other way around. We start with simple, contrived building blocks and slowly work our way up to the point where we can comfortably manipulate a more complex and realistic system.

For example, a course that teaches the principle of the “Time Value of Money” is likely to start with a question like “if someone offered you $90 today or $100 a year from now, which one would you take?” This is, to say the least, an unrealistic scenario. But it is an introduction into the concept. After working through a number of similar examples in order to allow the student to master the math, the course will hopefully move on to a more reasonable explanation of how this concept is used in practice.

By Anna reg (Own work) [GFDL or CC-BY-SA-3.0-at], via Wikimedia CommonsNot that it was a bad course. I actually quite liked it. But this would be like if Alfredo had first worked on pedals, then wheels, then built himself a unicycle before moving on to gears and brakes. It would have been years before he had anything he could ride on. Knowing Alfredo, he would have had no hope of staying motivated for such a long time with no bike to show for it.

Given how useful the tinkering approach is for keeping learners motivated, how do we apply a similar approach to Finance? It turns out this is difficult to do because it often involves risking real money and waiting years to see any results. What a learner really needs is a safe environment to develop intuition around the long-term consequences of her decisions and to discover for herself the places where she needs to dig deeper.

At Pedago, developing alternative approaches to teaching tough topics is what we’re passionate about. Stay tuned over the coming months to see us tackle similar problems.

This post has been updated to include a clearer example. Thanks to Earthling for the feedback!

“After forty years of intensive research on school learning in the United States as well as abroad, my major conclusion is: What any person in the world can learn, almost all persons can learn, if provided with the appropriate prior and current conditions of learning.”

“I do not wish to reduce mathematics to literature or literature to mathematics. But I do want to argue that their respective ways of thinking are not as separate as is usually supposed.” ~Seymour Papert.